Marginality indices for biodiversity conservation in forest trees

Marginal and peripheral populations are important for biodiversity conservation. Their original situation in a species geographic and ecological space often confers them genetic diversity and traits of high adaptive value. Yet theoretical hypotheses related to marginality are difficult to test because of confounding factors that influence marginality, namely environment, geography, and history. There is an urgent need to develop metrics to disentangle these confounding factors. We designed nine quantitative indices of marginality and peripherality that define where margins lie within species distributions, from a geographical, an environmental and a historical perspective. Using the distribution maps of eight European forest tree species, we assessed whether these indices were idiosyncratic or whether they conveyed redundant information. Using a database on marginal and peripheral populations based on expert knowledge, we assessed the capacity of the indices to predict the marginality status of a population. There was no consistent pattern of correlation between indices across species, confirming that the indices conveyed different information related to the specific geometry of the species distributions. Contrasting with this heterogeneity of correlation patterns across species, the relative importance of the indices to predict the marginality status of populations was consistent across species. However, there was still a significant country effect in the marginality status, showing a variation in expert opinion of marginality vis ' a-vis the species distribution. The marginality indices that we developed are entirely based on distribution maps and can be used for any species. They pave the way for testing hypotheses related to marginality and peripherality, with important implications in quantitative ecology, genetics, and biodiversity conservation.

Automated summary

Marginal and peripheral populations play a crucial role in biodiversity conservation. However, testing theoretical hypotheses related to marginality is challenging due to confounding factors. Nine quantitative indices were designed to assess marginality and peripherality, which showed promising predictive abilities for the marginality status of populations.